Modeling Employment and Automation in the United States

Ryu, Dennis

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https://hdl.handle.net/2142/99005 Copy

Description

Title

Modeling Employment and Automation in the United States

Author(s)

Ryu, Dennis

Contributor(s)

Varshney, Lav R.

Issue Date

2017-12

Keyword(s)

• job distance
• automation

Abstract

When people change jobs, it is useful for both employers and employees to find best-fit jobs on the basis of the employees’ skillsets. We utilize the O*NET database to introduce the notion of the job distance, which allows us to measure the difference between jobs based on the skillsets required to successfully perform them. We then apply this measure to data from the Bureau of Labor Statistics (BLS) to model the job distribution in each metropolitan or rural area. Novel graph metrics are found along the way, but we ultimately address the impact of automation by combining a gravity and Markov model.

Type of Resource

other

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http://hdl.handle.net/2142/99005

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